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Abstract

Motion planning and control involve mainly symbolic and subsymbolic processing, as does the learning of these capabilities. This paper focusses on a motion control aspect, namely, the learning of obstacle avoidance abilities. A reinforcement-based connectionist system is presented which is able to find and learn obstacle-avoiding paths for a mobile robot in a non-maze-like 2D environment. Some directions on how to interface the subsymbolic system developed with a symbolic path planner are provided.

Additional information

Authors: MILLAN J DEL R, JRC Ispra (IT);TORRAS C, Institut de Cibernètica, Barcelona (ES)
Bibliographic Reference: Paper presented: 8th International Workshop on Machine Learning, Evanston (US), June 27-29, 1991
Availability: Available from (1) as Paper EN 36198 ORA
Record Number: 199110843 / Last updated on: 1994-12-02
Category: PUBLICATION
Original language: en
Available languages: en